DS007445: ieeg dataset, 19 subjects#
Thalamocortical ictal iEEG dataset
Citation: Saarang Panchavati, Atsuro Daida, Sotaro Kanai, Shingo Oana, Hiroya Ono, Masaki Izumi, Kikuko Kaneko, Aria Fallah, Joe X Qiao, Noriko Salamon, Raman Sankar, Corey Arnold, William Speier, Hiroki Nariai (2026). Thalamocortical ictal iEEG dataset. 10.18112/openneuro.ds007445.v1.0.2
19-participant iEEG dataset — Thalamocortical ictal iEEG dataset.
Quickstart#
Install
pip install eegdash
Access the data
from eegdash.dataset import DS007445
dataset = DS007445(cache_dir="./data")
# Get the raw object of the first recording
raw = dataset.datasets[0].raw
print(raw.info)
Filter by subject
dataset = DS007445(cache_dir="./data", subject="01")
Advanced query
dataset = DS007445(
cache_dir="./data",
query={"subject": {"$in": ["01", "02"]}},
)
Iterate recordings
for rec in dataset:
print(rec.subject, rec.raw.info['sfreq'])
If you use this dataset in your research, please cite the original authors.
BibTeX
@dataset{ds007445,
title = {Thalamocortical ictal iEEG dataset},
author = {Saarang Panchavati and Atsuro Daida and Sotaro Kanai and Shingo Oana and Hiroya Ono and Masaki Izumi and Kikuko Kaneko and Aria Fallah and Joe X Qiao and Noriko Salamon and Raman Sankar and Corey Arnold and William Speier and Hiroki Nariai},
doi = {10.18112/openneuro.ds007445.v1.0.2},
url = {https://doi.org/10.18112/openneuro.ds007445.v1.0.2},
}
About This Dataset#
We investigated thalamocortical network dynamics using intracranial EEG (iEEG) recordings with thalamic sampling from 19 patients with focal epilepsy (1). The iEEG dataset analyzed in this study is publicly shared here.
BIDS converstion was performed according to references (2) and (3).
References
Panchavati S, Daida A, Kanai S, Oana S, Ono H, Izumi M, Kaneko K, Fallah A, Qiao JX, Salamon N, Sankar R, Arnold C, Speier W, Nariai H (2026). Distinct Spectral and Directional Thalamocortical Network Dynamics Define Focal Seizure Evolution. medRxiv, 2026 Feb 4:2026.02.03.26345480. doi: 10.64898/2026.02.03.26345480.
Appelhoff, S., Sanderson, M., Brooks, T., Vliet, M., Quentin, R., Holdgraf, C., Chaumon, M., Mikulan, E., Tavabi, K., Höchenberger, R., Welke, D., Brunner, C., Rockhill, A., Larson, E., Gramfort, A. and Jas, M. (2019). MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. Journal of Open Source Software 4: (1896).https://doi.org/10.21105/joss.01896
Holdgraf, C., Appelhoff, S., Bickel, S., Bouchard, K., D’Ambrosio, S., David, O., … Hermes, D. (2019). iEEG-BIDS, extending the Brain Imaging Data Structure specification to human intracranial electrophysiology. Scientific Data, 6, 102. https://doi.org/10.1038/s41597-019-0105-7
Cohort#
Dataset Statistics#
Age distribution by gender (n=1, range 73–73 yr, mean 73.0 yr)
Channel counts (ch)
Sampling frequencies (Hz)
Total recording duration: 73 h
Signal · Electrodes & live trace#
Live trace viewer — sub-019 · ses-sz3 · task-seizure
Showing one representative recording out of
19 subjects and 66 recordings in this dataset.
Browse the full set on OpenNeuro;
drop any other _ieeg.{set,edf,bdf,vhdr} file onto the
viewer (or pass ?ieeg=<url>) to inspect it.
No scalp electrode layout is currently indexed for this dataset. Once the eegdash montage registry ingests it, the interactive viewer will appear here automatically.
NEMAR Processing Statistics#
The plots below are generated by NEMAR’s automated EEG pipeline. The histogram shows pipeline success for data cleaning and ICA decomposition, the percentage of data frames and EEG channels retained after artefact removal, line noise per channel (RMS, dB), and the age/gender distribution of participants.
HED event descriptors word cloud
Manifest#
File Explorer#
Browse the BIDS file structure of this dataset. Records are fetched on demand from the EEGDash catalog the first time you open the explorer.
Full dataset metadata table
Dataset ID |
|
Title |
Thalamocortical ictal iEEG dataset |
Author (year) |
|
Canonical |
— |
Importable as |
|
Year |
2026 |
Authors |
Saarang Panchavati, Atsuro Daida, Sotaro Kanai, Shingo Oana, Hiroya Ono, Masaki Izumi, Kikuko Kaneko, Aria Fallah, Joe X Qiao, Noriko Salamon, Raman Sankar, Corey Arnold, William Speier, Hiroki Nariai |
License |
CC0 |
Citation / DOI |
|
Source links |
OpenNeuro | NeMAR | Source URL |
Copy-paste BibTeX
@dataset{ds007445,
title = {Thalamocortical ictal iEEG dataset},
author = {Saarang Panchavati and Atsuro Daida and Sotaro Kanai and Shingo Oana and Hiroya Ono and Masaki Izumi and Kikuko Kaneko and Aria Fallah and Joe X Qiao and Noriko Salamon and Raman Sankar and Corey Arnold and William Speier and Hiroki Nariai},
doi = {10.18112/openneuro.ds007445.v1.0.2},
url = {https://doi.org/10.18112/openneuro.ds007445.v1.0.2},
}
API Reference#
eegdash.datasetEEGDashDatasetDS007445 · Panchavati2026eegdash/dataset/registry.py · [source ↗]- class eegdash.dataset.DS007445(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#
Thalamocortical ictal iEEG dataset
- Study:
ds007445(OpenNeuro)- Author (year):
Panchavati2026- Canonical:
—
Also importable as:
DS007445,Panchavati2026.Modality:
ieeg; Experiment type:Clinical/Intervention; Subject type:Epilepsy. Subjects: 19; recordings: 66; tasks: 1.- Parameters:
cache_dir (str | Path) – Directory where data are cached locally.
query (dict | None) – Additional MongoDB-style filters to AND with the dataset selection. Must not contain the key
dataset.s3_bucket (str | None) – Base S3 bucket used to locate the data.
**kwargs (dict) – Additional keyword arguments forwarded to
EEGDashDataset.
- data_dir#
Local dataset cache directory (
cache_dir / dataset_id).- Type:
Path
Notes
Each item is a recording; recording-level metadata are available via
dataset.description.querysupports MongoDB-style filters on fields inALLOWED_QUERY_FIELDSand is combined with the dataset filter. Dataset-specific caveats are not provided in the summary metadata.References
OpenNeuro dataset: https://openneuro.org/datasets/ds007445 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds007445 DOI: https://doi.org/10.18112/openneuro.ds007445.v1.0.2
Examples
>>> from eegdash.dataset import DS007445 >>> dataset = DS007445(cache_dir="./data") >>> recording = dataset[0] >>> raw = recording.load()
- __init__(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#
- save(path: str, overwrite: bool = False, offset: int = 0)[source]#
Save datasets to files by creating one subdirectory for each dataset:
path/ 0/ 0-raw.fif | 0-epo.fif description.json raw_preproc_kwargs.json (if raws were preprocessed) window_kwargs.json (if this is a windowed dataset) window_preproc_kwargs.json (if windows were preprocessed) target_name.json (if target_name is not None and dataset is raw) 1/ 1-raw.fif | 1-epo.fif description.json raw_preproc_kwargs.json (if raws were preprocessed) window_kwargs.json (if this is a windowed dataset) window_preproc_kwargs.json (if windows were preprocessed) target_name.json (if target_name is not None and dataset is raw)
- Parameters:
path (str) –
- Directory in which subdirectories are created to store
-raw.fif | -epo.fif and .json files to.
overwrite (bool) – Whether to delete old subdirectories that will be saved to in this call.
offset (int) – If provided, the integer is added to the id of the dataset in the concat. This is useful in the setting of very large datasets, where one dataset has to be processed and saved at a time to account for its original position.
BaseDataset from braindecode — windowed via create_windows_from_events.braindecodeDataLoader; supports parallel workers and on-the-fly augmentations.pytorch
Find datasets with the EEGDash APIQuery the catalogue, filter by task or modality, list candidates.
Load one EEG recordingResolve a single record to an MNE Raw with channels and events.
EEG recording to PyTorch DataLoaderWrap braindecode windows in a DataLoader for model training.
Preprocess EEG and create windowsFilter, resample, epoch — and persist the windowed dataset.
Save and reload prepared dataCache a windowed dataset to disk and reattach it without recompute.
Download a dataset locallyPrefetch BIDS files to a local cache and validate the layout.Swap any load_dataset(...) call for ds007445 to reproduce the tutorial on this dataset.
Citation
Saarang Panchavati, Atsuro Daida, Sotaro Kanai, Shingo Oana, Hiroya Ono, … (2026). Thalamocortical ictal iEEG dataset. 10.18112/openneuro.ds007445.v1.0.2
Provenance
¹Contributed to openneuro in BIDS format.
²Curated & ingested by the EEGDash catalog; see CITATION.cff for canonical reference.
³Persistent identifier: 10.18112/openneuro.ds007445.v1.0.2.
See Also#
eegdash.dataset.EEGDashDataseteegdash.dataset